Analysis of ECG Measures of Cardiac Repolarization in Relation to Arrhythmic Events in an Implantable Cardioverter Defibrillator Population
Corresponding Author
Bijia Shi M.B.Ch.B., Ph.D.
Wellington Cardiovascular Research Group, Wellington, New Zealand
Department of Surgery and Anaesthesia, University of Otago, Wellington, New Zealand
Address for Correspondence: Bijia Shi, Department of Surgery and Anaesthesia. University of Otago Wellington, Mein Street, Newtown, Wellington, New Zealand. Fax: 64-4-389 5318; E-mail: [email protected]Search for more papers by this authorScott Harding M.B.Ch.B.
Wellington Cardiovascular Research Group, Wellington, New Zealand
Department of Cardiology, Wellington Regional Hospital, Wellington, New Zealand
Search for more papers by this authorPeter Larsen Ph.D.
Wellington Cardiovascular Research Group, Wellington, New Zealand
Department of Surgery and Anaesthesia, University of Otago, Wellington, New Zealand
Search for more papers by this authorCorresponding Author
Bijia Shi M.B.Ch.B., Ph.D.
Wellington Cardiovascular Research Group, Wellington, New Zealand
Department of Surgery and Anaesthesia, University of Otago, Wellington, New Zealand
Address for Correspondence: Bijia Shi, Department of Surgery and Anaesthesia. University of Otago Wellington, Mein Street, Newtown, Wellington, New Zealand. Fax: 64-4-389 5318; E-mail: [email protected]Search for more papers by this authorScott Harding M.B.Ch.B.
Wellington Cardiovascular Research Group, Wellington, New Zealand
Department of Cardiology, Wellington Regional Hospital, Wellington, New Zealand
Search for more papers by this authorPeter Larsen Ph.D.
Wellington Cardiovascular Research Group, Wellington, New Zealand
Department of Surgery and Anaesthesia, University of Otago, Wellington, New Zealand
Search for more papers by this authorAbstract
Background
ECG-derived measures of cardiac repolarization may have utility in risk prediction of future ventricular arrhythmia, and a range of different measures have been proposed. We compared time-based, vectorcardiographic, and singular value decomposition (SVD) derived measures of repolarization to determine which was most predictive of appropriate therapy in an ICD population.
Methods
We examined the independent prognostic value of a range of repolarization measures derived from 60 second 12-lead ECG recordings in 150 patients receiving new ICD implants in relation to the occurrence of appropriate therapy during follow-up.
Results
Over an average follow-up of 2.15 ± 0.87 years, male gender, presence of premature ventricular complex (PVC), relative T wave residuum (TWR-rel, measures regional repolarization heterogeneity), and TCRT (the total cosine R-to-T, describes the global angle between repolarization and depolarization wavefronts) were the only independent predictors of appropriate therapy. With every 0.01% increase in TWR-rel, there was 2% increased risk of appropriate therapy (HR = 1.02, 95% CI 1.006–1.034, P < 0.001). With every 1° decrease in TCRT, there was an increase in arrhythmic risk of 0.9% (HR 1.009, 95% CI 1.003–1.015, P = 0.003).
Conclusions
The use of advanced analytic ECG techniques to derive measures of repolarization abnormality might shave utility in risk stratification in an ICD population.
References
- 1Jin H, Lyon AR, Akar FG. Arrhythmia mechanisms in the failing heart. Pacing Clin Electrophysiol 2008; 31: 1048–1056.
- 2Akar FG, Rosenbaum DS. Transmural electrophysiological heterogeneities underlying arrhythmogenesis in heart failure. Circ Res 2003; 93: 638–645.
- 3Chauhan VS, Downar E, Nanthakumar K, et al. Increased ventricular repolarization heterogeneity in patients with ventricular arrhythmia vulnerability and cardiomyopathy: A human in vivo study. Am J Physiol Heart Circ Physiol 2006; 290: H79–H86.
- 4Goldberger JJ, Cain ME, Hohnloser SH, et al. American Heart Association/American College of Cardiology Foundation/Heart Rhythm Society Scientific Statement on Noninvasive Risk Stratification Techniques for Identifying Patients at Risk for Sudden Cardiac Death: A Scientific Statement From the American Heart Association Council on Clinical Cardiology Committee on Electrocardiography and Arrhythmias and Council on Epidemiology and Prevention. Circulation 2008; 118: 1497–1518.
- 5Acar B, Yi G, Hnatkova K, et al. Spatial, temporal and wavefront direction characteristics of 12-lead T-wave morphology. Med Biol Eng Comput 1999; 37: 574–584.
- 6Porthan K, Viitasalo M, Jula A, et al. Predictive value of electrocardiographic QT interval and T-wave morphology parameters for all-cause and cardiovascular mortality in a general population sample. Heart Rhythm 2009; 6: 1202–1208.
- 7Zabel M, Acar B, Klingenheben T, et al. Analysis of 12-lead T-wave morphology for risk stratification after myocardial infarction. Circulation 2000; 102: 1252–1257.
- 8Zabel M, Malik M, Hnatkova K, et al. Analysis of T-wave morphology from the 12-lead electrocardiogram for prediction of long-term prognosis in male US veterans. Circulation 2002; 105: 1066–1070.
- 9Huang HC, Lin LY, Yu HY, et al. Risk stratification by T-wave morphology for cardiovascular mortality in patients with systolic heart failure. Europace 2009; 11: 1522–1528.
- 10Davey P. QT interval and mortality from coronary artery disease. Prog Cardiovasc Dis 2000; 42: 359–384.
- 11Malik M, Acar B, Gang Y, et al. QT dispersion does not represent electrocardiographic interlead heterogeneity of ventricular repolarization. J Cardiovasc Electrophysiol 2000; 11: 835–843.
- 12Morin DP, Saad MN, Shams OF, et al. Relationships between the T-peak to T-end interval, ventricular tachyarrhythmia, and death in left ventricular systolic dysfunction. Europace 2012; 14: 1172–1179.
- 13Yan G-X, Antzelevitch C. Cellular basis for the normal T Wave and the electrocardiographic manifestations of the long-QT syndrome. Circulation 1998; 98: 1928–1936.
- 14Hetland M, Haugaa KH, Sarvari SI, et al. A novel ECG-index for prediction of ventricular arrhythmias in patients after myocardial infarction. Ann Noninvasive Electrocardiol 2014; 19: 330–337.
- 15Borleffs CJW, Scherptong RWC, Man S-C, et al. Predicting ventricular arrhythmias in patients with ischemic heart disease: Clinical application of the ECG-derived QRS-T angle. Circ Arrhythm Electrophysiol 2009; 2: 548–554.
- 16Pavri BB, Hillis MB, Subacius H, et al. Prognostic value and temporal behavior of the planar QRS-T angle in patients with nonischemic cardiomyopathy. Circulation 2008; 117: 3181–3186.
- 17Webber MR, Stiles MK. Recommendations for the programming of implantable cardioverter-defibrillators in New Zealand. Heart Lung Circ 2012; 21: 765–777.
- 18Jane R, Rix H, Caminal P, et al. Alignment methods for averaging of high-resolution cardiac signals: A comparative study of performance. IEEE Trans Biomed Eng 1991; 38: 571–579.
- 19Woody C. Characterization of an adaptive filter for the analysis of variable latency neuroelectric signals. Med Biol Eng Compu 1967; 5: 539–554.
- 20Fridericia LS. Die Systolendauer im Elektrokardiogramm bei normalen Menschen und bei Herzkranken. Acta Med Scand 1921; 54: 17–50.
10.1111/j.0954-6820.1921.tb15167.x Google Scholar
- 21Scherptong RW, Henkens IR, Man SC, et al. Normal limits of the spatial QRS-T angle and ventricular gradient in 12-lead electrocardiograms of young adults: Dependence on sex and heart rate. J Electrocardiol 2008; 41: 648–655.
- 22Schreurs CA, Algra AM, Man SC, et al. The spatial QRS-T angle in the Frank vectorcardiogram: Accuracy of estimates derived from the 12-lead electrocardiogram. J Electrocardiol 2010; 43: 294–301.
- 23Okin PM, Malik M, Hnatkova K, et al. Repolarization abnormality for prediction of all-cause and cardiovascular mortality in American Indians: The Strong Heart Study. [Erratum appears in J Cardiovasc Electrophysiol. 2005 Sep; 16(9):937]. J Cardiovasc Electrophysiol 2005; 16: 945–951.
- 24Okin PM, Devereux RB, Fabsitz RR, et al. Principal component analysis of the T Wave and prediction of cardiovascular mortality in American Indians: The Strong Heart Study. Circulation 2002; 105: 714–719.
- 25Lin Y-H, Lin L-Y, Chen Y-S, et al. The association between T-wave morphology and life-threatening ventricular tachyarrhythmias in patients with congestive heart failure. Pacing Clin Electrophysiol 2009; 32: 1173–1177.
- 26Batchvarov V, Hnatkova K, Ghuran A, et al. Ventricular gradient as a risk factor in survivors of acute myocardial infarction. Pacing Clin Electrophysiol 2003; 26: 373–376.
- 27Perkiömäki JS, Hyytinen-Oinas M, Karsikas M, et al. Usefulness of T-Wave loop and QRS complex loop to predict mortality after acute myocardial infarction. Am J Cardiol 2006; 97: 353–360.
- 28Malik M. Nondipolar electrocardiographic components and myocardial heterogeneity. Ann Noninvasive Electrocardiol 2009; 14: 103–107.
- 29Kesek M, Gustavsson O, Wiklund U. Nondipolar content of T wave derived from a myocardial source simulation with increased repolarization inhomogeneity. Ann Noninvasive Electrocardiol 2009; 14: 185–192.
- 30Kardys I, Kors JA, van der Meer IM, et al. Spatial QRS-T angle predicts cardiac death in a general population. Eur Heart J 2003; 24: 1357–1364.
- 31Bastiaenen R, Batchvarov V, Gallagher MM. Ventricular automaticity as a predictor of sudden death in ischaemic heart disease. Europace 2012; 14: 795–803.
- 32Berkowitsch A, Zareba W, Neumann T, et al. Risk stratification using heart rate turbulence and ventricular arrhythmia in MADIT II: Usefulness and limitations of a 10-minute Holter recording. Ann Noninvasive Electrocardiol 2004; 9: 270–279.
- 33Taylor E, Berger R, Hummel JD, et al. Analysis of the pattern of initiation of sustained ventricular arrhythmias in patients with implantable defibrillators. J Cardiovasc Electrophysiol 2000; 11: 719–726.
- 34Rosman J, Hanon S, Shapiro M, et al. Triggers of sustained monomorphic ventricular tachycardia differ among patients with varying etiologies of left ventricular dysfunction. Ann Noninvasive Electrocardiol 2006; 11: 113–117.
- 35Anthony R, Daubert JP, Zareba W, et al. Mechanisms of ventricular fibrillation initiation in MADIT II patients with implantable cardioverter defibrillators. Pacing Clin Electrophysiol 2008; 31: 144–150.
- 36van der Heijden AC, Thijssen J, Borleffs CJ, et al. Gender-specific differences in clinical outcome of primary prevention implantable cardioverter defibrillator recipients. Heart 2013; 99: 1244–1249.
- 37Bhavnani SP, Pavuluri V, Coleman CI, et al. The gender-paradox among patients with implantable cardioverter-defibrillators: A propensity-matched study. Pacing Clin Electrophysiol 2013; 36: 878–884.
- 38Lampert R, McPherson CA, Clancy JF, et al. Gender differences in ventricular arrhythmia recurrence in patients with coronary artery disease and implantable cardioverter-defibrillators. J Am Coll Cardiol 2004; 43: 2293–2299.
10.1016/j.jacc.2004.03.031 Google Scholar
- 39Santangeli P, Pelargonio G, Dello Russo A, et al. Gender differences in clinical outcome and primary prevention defibrillator benefit in patients with severe left ventricular dysfunction: A systematic review and meta-analysis. Heart Rhythm 2010; 7: 876–882.
- 40Ghanbari H, Dalloul G, Hasan R, et al. Effectiveness of implantable cardioverter-defibrillators for the primary prevention of sudden cardiac death in women with advanced heart failure: A meta-analysis of randomized controlled trials. Arch Intern Med 2009; 169: 1500–1506.
- 41Albert CM, Quigg R, Saba S, et al. Sex differences in outcome after implantable cardioverter defibrillator implantation in nonischemic cardiomyopathy. Am Heart J 2008; 156: 367–372.
- 42Piro M, Della Bona R, Abbate A, et al. Sex-related differences in myocardial remodeling. J Am Coll Cardiol 2010; 55: 1057–1065.
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